Data Scientist, Revenue and Reporting

San Francisco or Seattle

Applications have closed

Stripe

Stripe powers online and in-person payment processing and financial solutions for businesses of all sizes. Accept payments, send payouts, and automate financial processes with a suite of APIs and no-code tools.

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Generate insights and impact from data.

 We're looking for data scientists to join the Data Science team who are excited about applying their analytical skills to understand our users and influence decision making. If you are naturally data curious, excited about deriving insights from data, and motivated by having impact on the business, we want to hear from you.

Stripe builds the most powerful and flexible products for running an internet business. We handle billions of dollars each year and enable millions of users around the world to scale faster and more efficiently by building their businesses on Stripe. Sitting atop our payments platform are applications to manage revenue, prevent fraud, expand internationally, and many others. 

You’ll be working with the Revenue and Reporting team to build and optimize a suite of holistic revenue management products for ambitious internet businesses, including subscriptions, invoice generation and reconciliation, business analytics, reporting and integration with third-party accounting systems—a robust set of building blocks which may be combined in creative ways to run almost any type of business on Stripe. In this role, you’ll partner closely with Product, Engineering, UX Research, Marketing, Sales, Finance and Data Science teams to establish a rigorous analytical foundation for decision making. You will build tools and analyses that will inform the entire product lifecycle, from product strategy, go-to-market and pricing to optimizing user experience and growing product adoption post-launch. 

 You will:

  • Partner closely with Product, Engineering, UX Research, Marketing, Sales, Finance and Data Science teams to shape product strategy using rigorous scientific solutions
  • Apply statistical, machine learning and econometric models on large datasets to: i) measure results and outcomes, ii) identify causal impact and attribution, iii) predict future performance of users or products
  • Design, analyze, and interpret the results of experiments
  • Design, implement and launch innovative data science solutions to empower data-driven decisions at scale
  • Drive the collection of new data and the refinement of existing data sources
  • Create analyses that tell a “story” focused on insights, not just data

We're looking for someone with:

  • 6+ years of data science experience with a track record of leadership and innovation
  • A PhD or MS in a quantitative field (e.g., Economics, Statistics, Engineering, Natural Sciences)
  • Expert knowledge of a scientific computing language (such as R or Python) and SQL
  • Strong theoretical and applied expertise in statistics, experimentation, and machine learning
  • Demonstrated track record of identifying, scoping and leading complex data science projects with cross-functional partners and high business impact
  • Ability to synthesize complex quantitative analysis in a clear, precise, and actionable manner to both technical and non-technical audiences

 Nice to haves:

  • Experience working with a user-facing product team
  • Prior experience with data-distributed tools (Scalding, Spark, Hadoop, Pig, etc)

You should include these in your application:

  • Resume and LinkedIn profile

Tags: Business Analytics Economics Engineering Finance Hadoop Machine Learning PhD Python R Research Spark SQL Statistics UX UX Research

Perks/benefits: Flex hours

Region: North America
Country: United States
Job stats:  21  2  0
Category: Data Science Jobs

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